IEEE

Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds

Abstract: Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. With ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Efficient Group Cosine Convolutional Neural Network for EEG-Based Seizure Identification

Abstract: Epilepsy is a common neurological disease, and its diagnosis usually depends on labor-intensive visual inspection of electroencephalogram (EEG). Although various deep learning-based seizure ...